collaborators

5 papers

cs.AI2026

Towards Agentic Agent-based Models: Feasibility, Performance, and Statistical Model Checking

Stefano Blando, Emanuele Guerrazzi, Riccardo Porcedda +3

Agent-based models (ABMs) rely on simple, explicit and reproducible rules for individual decision making, while complex collective behavior emerges from interactions among agents.…

cs.DC2026

Scaling Weisfeiler-Leman Expressiveness Analysis to Massive Graphs with GPUs

Filippo Biondi, Mirco Tribastone, Max Tschaikowski

The stable coloring of the Weisfeiler-Leman (1-WL) test is a cornerstone of Graph Neural Networks because it provides an upper bound to the expressive power of message-passing arch…

quant-ph2026

Constrained Quantum Optimization meets Model Reduction

Max Tschaikowski, Andrea Vandin

Quantum optimization algorithms promise advantages for difficult problems but are costly to simulate and analyze on classical machines. Recently, constrained quantum optimization h…

cs.SI2024

Efficient Network Embedding by Approximate Equitable Partitions

Giuseppe Squillace, Mirco Tribastone, Max Tschaikowski +1

Structural network embedding is a crucial step in enabling effective downstream tasks for complex systems that aims to project a network into a lower-dimensional space while preser…

cs.CE2024

Approximate Constrained Lumping of Chemical Reaction Networks

Alexander Leguizamon-Robayo, Antonio Jiménez-Pastor, Micro Tribastone +2

Gaining insights from realistic dynamical models of biochemical systems can be challenging given their large number of state variables. Model reduction techniques can mitigate this…